Application of Hjorth parameters in the classification of healthy aging EEG signals

Application of Hjorth parameters in the classification of healthy aging EEG signals

Aging has extensive impacts on brain cognition. In this work we proposed a method using Hjorth parameters to classify the elderly’s electroencephalography (EEG) signals from that of middle age group by applying K-nearest neighbor (KNN) and Random forest (RF) classifiers. We acquired EEG of 20 heal...

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Bibliographic Details
Main Authors: Hamad Javaid, Krit Charupanit, Ekkasit Kumarnsit, Surapong Chatpun
Format: Article
Language:English
Published: Prince of Songkla University 2021-12-01
Series:Songklanakarin Journal of Science and Technology (SJST)
Subjects:
electroencephalography
aging
hjorth parameters
k-nearest neighbor
classification
Online Access:https://rdo.psu.ac.th/sjst/journal/43-6/37.pdf

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